Study on Hydrate Production Behaviors by Depressurization Combined with Brine Injection in the Excess-Water Hydrate Reservoir.

Depressurization combined with brine injection is a potential method for field production of natural gas hydrate, which can significantly improve production efficiency and avoid secondary formation of hydrate. In this work, the experiments of hydrate production using depressurization combined with brine injection from a simulated excess-water hydrate reservoir were performed, and the effects of NaCl concentration on hydrate decomposition, temperature change, and heat transfer in the reservoir were investigated. The experimental results indicate that there is little gas production during depressurization in a excess-water hydrate reservoir, and the gas dissociated from hydrate is trapped in pores of sediments. The high-water production reduces the final gas recovery, which is lower than 70% in the experiments. The increasing NaCl concentration only effectively promotes gas production rate in the early stage. The final cumulative gas production and average gas production rate have little difference in different experiments. The NaCl concentration of the produced water is significantly higher than that which is in contact with hydrate in the sediments because the water produced by hydrate decomposition exists on the surface of undissociated hydrate. The high concentration of NaCl in the produced water from the reactor significantly reduces the promoting effect and efficiency of NaCl solution on hydrate decomposition. The injection of NaCl solution decreases the lowest temperature in sediments during hydrate production, and increases the sensible heat and heat transfer from environment for hydrate decomposition. The changes of temperature and resistance effectively reflect the distribution of the injected NaCl solution in the hydrate reservoir.

STAT3 and SPI1, may lead to the immune system dysregulation and heterotopic ossification in ankylosing spondylitis.

OBJECTIVE: This study was aimed to identify the biomarkers for diagnosis and reveal the immune microenvironment changes in ankylosing spondylitis (AS). METHODS: GSE73754 was downloaded for the co-expression network construction and immune cell analyses. Flow cytometric analysis was performed to validate the results of bioinformatics analysis. Gene set enrichment analysis (GSEA) was performed to investigate the potential biological characteristic between different phenotypes. Pearson correlation analysis between the hub genes and the xCell score of immune cell types was performed. RESULTS: Signal transducer and activator of transcription 3 (STAT3) and Spi-1 proto-oncogene (SPI1) was identified as the hub genes in the datasets GSE73754. And the t-test showed that the expression level of STAT3 and SPI1 in the GSE73754 was significantly higher in AS and human leukocyte antigen (HLA)-B27(+) groups. Flow cytometric analysis showed that natural killer T cells (NKT) cells were upregulated, while Th1 cells were down-regulated in AS, which was consistent with the results obtained from bioinformatics analysis. STAT3 and SPI1 was correlated with the NKT cells and Th1 cells. CONCLUSION: STAT3 and SPI1 may be a key cytokine receptor in disease progression in AS.

STAT1 and CXCL10 involve in M1 macrophage polarization that may affect osteolysis and bone remodeling in extrapulmonary tuberculosis.

OBJECTIVE: This study was aimed to reveal the molecular mechanism of bone destruction due to macrophage polarization leading to during extrapulmonary tuberculosis (EPTB) infection. METHODS: The dataset GSE83456 was downloaded from the GEO database, and the xCell tool was used to obtain the 64 types of immune cells. The flow cytometry was performed to identified the differences between M1 and M2 macrophages between EPTB and the healthy controls (HCs). The enrichment analyses were performed on the differentially expressed genes (DEGs) and their functionally related modules. The hub genes were screened out, and their relationships with EPTB and the immune cell subtypes were further analyzed. RESULTS: The flow cytometric analysis validated this hypothesis of M1-macrophage polarization correlated with the pathogenesis of EPTB. Of the obtained 103 DEGs, 97 genes were upregulated, and 6 genes were downregulated. The GO and KEGG pathway analyses showed that the DEGs were particularly involved in the immune-related processes. The hub genes (STAT1 and CXCL10) might be involved in M1-macrophage polarization and correlated with the pathogenesis of EPTB. STAT1 and CXCL10 could also behave as biomarkers for EPTB. CONCLUSION: STAT1 and CXCL10 were involved in the M1-macrophage polarization and correlated with the pathogenesis of EPTB. Besides, both of them could also behave as biomarkers for EPTB diagnosis and provide the required clues for targeted therapy in the future.

Epithelial-mesenchymal transition interaction with CD8+ T cell, dendritic cell and immune checkpoints in the development of melanoma.

BACKGROUND: Melanoma is fatal cancer originating from melanocytes, whose high metastatic potential leads to an extremely poor prognosis. OBJECTIVE: This study aimed to reveal the relationship among EMT, TIICs, and immune checkpoints in melanoma. METHODS: Gene expression data and clinical data of melanoma were downloaded from TCGA, UCSC Xena and GEO databases. EMT-related DEGs were detected for risk score calculation. "ESTIMATE" and "xCell" were used for estimating TIICs and obtaining 64 immune cell subtypes, respectively. Moreover, we evaluated the relationship between the risk score and immune cell subtypes and immune checkpoints. RESULTS: Seven EMT-related genes were selected to establish a risk scoring system because of their integrated prognostic relevance. The results of GSEA revealed that most of the gene sets focused on immune-related pathways in the low-risk score group. The risk score was significantly correlated with the xCell score of some TIICs, which significantly affected the prognosis of melanoma. Patients with a low-risk score may be associated with a better response to ICI therapy. CONCLUSION: The individualized risk score could effectively conduct risk stratification, overall survival prediction, ICI therapy prediction, and TME judgment for patients with melanoma, which would be conducive to patients' precise treatment.

Ferroptosis-related gene SOCS1, a marker for tuberculosis diagnosis and treatment, involves in macrophage polarization and facilitates bone destruction in tuberculosis.

This study was aimed to reveal the role of ferroptosis in tuberculosis infection. To elucidate the ferroptosis-related DEGs, GEO datasets associated with tuberculosis infection were downloaded. The two external validation GEO datasets were exploited for subsequent verification of the ferroptosis-related DEGs. We further evaluated the correlation among the ferroptosis-related DEGs, therapeutic effects, and drug resistance. Finally, we tried to reveal the engagement of the ferroptosis-related DEGs in bone destruction during TB infection. The present study identified SOCS1 as the only ferroptosis-related DEGs. Compared to the non-TB patients, up-regulation of SOCS1 was evident in the TB patients. After receiving standard anti-TB treatment, significant down-regulation of SOCS1 confirmed its acceptance as the marker for therapeutic efficacy. The involvement of SOCS1 has also been suggested in the regulation of the micro immune environment in TB. Furthermore, SOCS1 might play an important role in causing bone destruction during TB infection. FRGs-SOCS1 may be the key gene involved in the pathogenesis and progression of TB infection.

Platelet-to-Lymphocyte Ratio as an Independent Factor Was Associated With the Severity of Ankylosing Spondylitis.

The study was aimed to determine the association of the platelet-lymphocyte ratio (PLR) with the disease activity of ankylosing spondylitis (AS). A total of 275 patients, including 180 AS patients and 95 non-AS patients, participated in the study. We assessed a full blood count for each participant. Platelet to monocyte ratio (PMR), monocytes to lymphocyte ratio (MLR), monocyte to neutrophil ratio (MNR), platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), and platelet to neutrophil ratio (PNR) were calculated. LASSO and logistic regression analyses were performed to establish the nomogram. Receiver operating characteristic (ROC) analysis was performed to evaluate the clinical value of the nomogram. We constructed a novel nomogram, which incorporated easily accessible clinical characteristics like sex, PLR, WBC, EOS, and ESR for AS diagnosis. The AUC value of this nomogram was 0.806; also, the calibration curves indicated a satisfactory agreement between nomogram prediction and actual probabilities. Furthermore, PLR was positively correlated with the severity of AS. PLR was identified as an independent factor for the diagnosis of AS and was associated with the severity of AS.

TYROBP, TLR4 and ITGAM regulated macrophages polarization and immune checkpoints expression in osteosarcoma.

We established a relationship among the immune-related genes, tumor-infiltrating immune cells (TIICs), and immune checkpoints in patients with osteosarcoma. The gene expression data for osteosarcoma were downloaded from UCSC Xena and GEO database. Immune-related differentially expressed genes (DEGs) were detected to calculate the risk score. "Estimate" was used for immune infiltrating estimation and "xCell" was used to obtain 64 immune cell subtypes. Furthermore, the relationship among the risk scores, immune cell subtypes, and immune checkpoints was evaluated. The three immune-related genes (TYROBP, TLR4, and ITGAM) were selected to establish a risk scoring system based on their integrated prognostic relevance. The GSEA results for the Hallmark and KEGG pathways revealed that the low-risk score group exhibited the most gene sets that were related to immune-related pathways. The risk score significantly correlated with the xCell score of macrophages, M1 macrophages, and M2 macrophages, which significantly affected the prognosis of osteosarcoma. Thus, patients with low-risk scores showed better results with the immune checkpoints inhibitor therapy. A three immune-related, gene-based risk model can regulate macrophage activation and predict the treatment outcomes the survival rate in osteosarcoma.

Immune status changing helps diagnose osteoarticular tuberculosis.

OBJECTIVE: This study is aimed to develop a new nomogram for the clinical diagnosis of osteoarticular tuberculosis (TB). METHODS: xCell score estimation to obtained the immune cell type abundance scores. We downloaded the expression profile of GSE83456 from GEO and proceed xCell score estimation. The routine blood examinations of 326 patients were collected for further validation. We analyzed univariate and multivariate logistic regression to identified independent predicted factor for developing the nomogram. The performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves. The correlation of ESR with lymphocytes, monocytes, and ML ratio was performed and visualized in osteoarticular TB patients. RESULTS: Compared with the healthy control group in the dataset GSE83456, the xCell score of basophils, monocytes, neutrophils, and platelets was higher, while lymphoid was lower in the EPTB group. The clinical data showed that the cell count of monocytes were much higher, while the cell counts of lymphocytes were lower in the osteoarticular TB group. AUCs of the nomogram was 0.798 for the dataset GSE83456, and 0.737 for the clinical data. We identified the ML ratio, BMI, and ESR as the independent predictive factors for osteoarticular TB diagnosis and constructed a nomogram for the clinical diagnosis of osteoarticular TB. AUCs of this nomogram was 0.843. CONCLUSIONS: We demonstrated a significant change between the ML ratio of the EPTB and non-TB patients. Moreover, we constructed a nomogram for the clinical diagnosis of the osteoarticular TB diagnosis, which works satisfactorily.

Is there a correlation between upper lumbar disc herniation and multifidus muscle degeneration? A retrospective study of MRI morphology.

BACKGROUND: The purpose of the study is to investigate the correlation between upper lumbar disc herniation (ULDH) and multifidus muscle degeneration via the comparison of width, the cross-sectional area and degree of fatty infiltration of the lumbar multifidus muscle. METHODS: Using the axial T2-weighted images of magnetic resonance imaging as an assessment tool, we retrospectively investigated 132 patients with ULDH and 132 healthy individuals. The total muscle cross-sectional area (TMCSA) and the pure muscle cross-sectional area (PMCSA) of the multifidus muscle at the L1/2, L2/3, and L3/4 intervertebral disc levels were measured respectively, and in the meantime, the average multifidus muscle width (AMMW) and degree of fatty infiltration of bilateral multifidus muscle were evaluated. The resulting data were analyzed to determine the presence/absence of statistical significance between the study and control groups. Multivariate logistical regression analyses were used to evaluate the correlation between ULDH and multifidus degeneration. RESULTS: The results of the analysis of the two groups showed that there were statistically significant differences (p < 0.05) between TMCSA, PMCSA, AMMW and degree of fatty infiltration. The multivariate logistic regression analysis indicated that the TMCSA, PMCSA, AMMW and the degree of fatty infiltration of multifidus muscle were correlated with ULDH, and the differences were statistically significant (P < 0.05). CONCLUSIONS: A correlation could exist between multifidus muscles degeneration and ULDH, that may be a process of mutual influence and interaction. Lumbar muscle strengthening training could prevent and improve muscle atrophy and degeneration.

Establishment of immune prognostic signature and analysis of prospective molecular mechanisms in childhood osteosarcoma patients.

BACKGROUND: In pediatric tumors, immunotherapy exhibits less toxicity than chemotherapy and radiation. The current study aims to identify potential immune targets in immune-related genes of C-C motif chemokine ligand genes (CCLs) and C-C motif chemokine receptors (CCRs) in childhood osteosarcoma (OS) and to explore the underlying molecular mechanisms of childhood OS. METHODS: Firstly, we identified immune-related genes in CCLs and CCRs, these genes were used for functional annotation and interaction analysis. Then, the prognostic value of these genes was evaluated using Kaplan-Meier analysis and multivariate COX regression model. And the potential relationship between risk score and immune infiltrating cells was identified. Finally, gene set enrichment analysis was used to determine the underlying molecular mechanism of OS. Immune-related genes in CCLs and CCRs are inextricably linked. RESULTS: The results of survival analysis of these genes show that CCL5, CCL8, CCR4, and CCR5 are significantly associated with the prognosis of childhood OS. The combined effect survival analysis shows that the co-high expression of these 4 genes has a good prognosis for childhood OS. A prognostic signature model was constructed based on the 4 genes mentioned above, and the result of time-dependent receiver operating characteristic curves showed that this model was a good predictor of childhood OS 3- and 5-year prognosis. In addition, the risk score of the constructed prognostic signature model was closely related to immune infiltration. We also found that CCL5, CCL8, and CCR5 may affect the prognosis of OS through complex regulation among Toll-like receptor signaling pathway, mitogen-activated protein kinase (MAPK) family signaling cascade, and nuclear factor-kappaB pathway, whereas CCR4 affects the prognosis of OS by regulating eukaryotic translation. CONCLUSION: CCL5, CCL8, CCR4, and CCR5 are potential prognostic markers for the prognosis of childhood OS, and the underlying molecular mechanisms of childhood OS have been identified.

KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining.

BACKGROUND: The incidence of triple negative breast cancer (TNBC) is at a relatively high level, and our study aimed to identify differentially expressed genes (DEGs) in TNBC and explore the key pathways and genes of TNBC. METHODS: The gene expression profiling (GSE86945, GSE86946 and GSE102088) data were obtained from Gene Expression Omnibus Datasets, DEGs were identified by using R software, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools, and the protein-protein interaction (PPI) network of the DEGs was constructed by the STRING database and visualized by Cytoscape software. Finally, the survival value of hub DEGs in breast cancer patients were performed by the Kaplan-Meier plotter online tool. RESULTS: A total of 2998 DEGs were identified between TNBC and health breast tissue, including 411 up-regulated DEGs and 2587 down-regulated DEGs. GO analysis results showed that down-regulated DEGs were enriched in gene expression (BP), extracellular exosome (CC), and nucleic acid binding, and up-regulated were enriched in chromatin assembly (BP), nucleosome (CC), and DNA binding (MF). KEGG pathway results showed that DEGs were mainly enriched in Pathways in cancer and Systemic lupus erythematosus and so on. Top 10 hub genes were picked out from PPI network by connective degree, and 7 of top 10 hub genes were significantly related with adverse overall survival in breast cancer patients (P < .05). Further analysis found that only EGFR had a significant association with the prognosis of triple-negative breast cancer (P < .05). CONCLUSIONS: Our study showed that DEGs were enriched in pathways in cancer, top 10 DEGs belong to up-regulated DEGs, and 7 gene connected with poor prognosis in breast cancer, including HSP90AA1, SRC, HSPA8, ESR1, ACTB, PPP2CA, and RPL4. These can provide some guidance for our research on the diagnosis and prognosis of TNBC, and further research is needed to evaluate their value in the targeted therapy of TNBC.

Gene expression profile and bioinformatics analysis revealed key molecular characteristics of chordoma-before and after TNF- a treatment.

BACKGROUND: Chordoma is a rare malignant tumor with limited treatment. Recent studies have shown that the proliferation and invasion ability of chordoma after Tumor necrosis factor alpha (TNF-α) treatment is enhanced, which may activate the gene pathway involved in the development of chordoma. This study tends to identify differentially expressed genes (DEGs) before and after treatment of TNF-α in chordoma cell line, providing a new target for future molecular therapy of chordoma. METHODS: The gene expression profile of GSE101867 was downloaded from the Gene Expression Omnibus database, and the differentially expressed genes were obtained using GEO2R. Based on the CLUEGO plugin in Cytoscape, DEGs functionality and enrichment analysis. A protein-protein interaction (PPI) network was constructed using Cytoscape based on data collected from the STRING online dataset. The Hub genes are selected from the CytoHubba, the first 20 genes that coexist with the KEGG tumor-related pathway. RESULTS: A total of 560 genes, including 304 up-regulated genes and 256 down-regulated genes, were selected as DEGs. Obviously, GO analysis shows that up-regulated and down-regulated DEGs are mainly enriched in biological processes such as synaptic tissue, cell adhesion, extracellular matrix organization and skeletal system development. DEGs are mainly enriched in tumor-associated pathways such as Pi3k-akt Signal path, Rap1 signal path. Three key genes were identified: PDGFRB, KDR, FGF2. All of these genes are involved in the tumor-associated pathways described previously. CONCLUSION: This study is helpful in understanding the molecular characteristics of chordoma development. Hub genes PDGFRB, KDR, FGF2 and pi3k-akt signaling pathway, Rap1 signaling pathway will become a new target for the future treatment of chordoma.

KEGG-expressed genes and pathways in intervertebral disc degeneration: Protocol for a systematic review and data mining.

miRNAs and genes play significant roles in the etiology and pathogenesis of intervertebral disc degeneration (IDD). This study aimed to identify aberrantly expressed miRNAs, genes, and pathways in IDD through a comprehensive bioinformatics analysis.Data of miRNAs expression microarrays (GSE63492) and genes microarrays (GSE23130) were obtained from GEO database. Similarly, aberrantly expressed miRNAs and genes were obtained using GEO2R. In addition, functional and enrichment analyses of selected miRNAs and genes were performed using the DAVID database. Meanwhile, protein-protein interaction (PPI) network was constructed using STRING, and then visualized in Cytoscape.A total of 98 upregulated miRNAs were identified. They were enriched in biological processes of response to organelle, ion binding, cellular nitrogen compound metabolic process, biosynthetic process, small molecule metabolic process, cellular protein modification process, catabolic process, molecular function, neurotrophin TRK receptor signaling pathway, and protein complex. In addition, 1405 high expression protein genes were detected. It indicated enrichment in biological processes, such as translational initiation, nonsense-mediated decay, viral transcription, cell-cell adhesion, rRNA processing, translation, RP-dependent cotranslational protein targeting to membrane, nuclear-transcribed mRNA catabolic process, regulation of mRNA stability, and mRNA splicing via spliceosome and extracellular matrix organization. In addition, pathway analysis exhibited the common enrichment in focal adhesion, Hippo signaling pathway, ECM-receptor interaction, Wnt signaling pathway, PI3K-Akt signaling pathway, endocytosis, proteoglycans in cancer, and so on. The top 10 central genes of PPI network were POTEE, PPP2CA, RPL17, HSP90AA1, POTEF, RPL13A, ACTB, RPL18, RPS24, and HSPA1A.In conclusion, our research proposed abnormally expressed miRNAs, genes, and pathways in IDD through bioinformatics methods, which may provide new insights into the pathogenesis of IDD. Thus, the Hub gene involving POTEE, PPP2CA, RPL17, HSP90AA1, POTEF, RPL13A, ACTB, RPL18, RPS24, and HSPA1A may be biomarkers for accurate diagnosis and treatment of IDD in the future.

Broad-Specificity Chemiluminescence Enzyme Immunoassay for (Fluoro)quinolones: Hapten Design and Molecular Modeling Study of Antibody Recognition.

On the basis of the structural features of (fluoro)quinolones (FQs), pazufloxacin was first used as a generic immunizing hapten to raise a broad-specificity antibody. The obtained polyclonal antibody exhibited broad cross-reactivity ranging from 5.19% to 478.77% with 21 FQs. Furthermore, the antibody was able to recognize these FQs below their maximum residue limits (MRLs) in an indirect competitive chemiluminescence enzyme immunoassay (ic-CLEIA), with the limit of detection (LOD) ranging from 0.10 to 33.83 ng/mL. For simply pretreated milk samples with spiked FQs, the ic-CLEIA exhibited an excellent recovery with a range of 84.6-106.9% and an acceptable coefficient of variation below 15%, suggesting its suitability and reliability for the use of a promising tool to detect FQs. Meanwhile, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models, with statistically significant correlation coefficients (q(2)CoMFA = 0.559, r(2)CoMFA = 0.999; q(2)CoMSIA = 0.559, r(2)CoMSIA = 0.994), were established to investigate the antibody recognition mechanism. These two models revealed that in the antibody, the active cavity binding FQs' 7-position substituents worked together with another cavity (binding FQs' 1-position groups) to crucially endow the high cross-reactivity. This investigation will be significant for better exploring the recognition mechanism and for designing new haptens.